Most early stage companies are now doing the same thing as well. It's basically a re-invention of the "build fast and test" model that was the norm amongst startups in the late 2000s and early 2010s.
Yes it led to some degree of tech debt, but it also made it easier to experiment, validate, and identify good and bad workflows.
At least in my network, we don't think AI will replace all workers and we strongly believe AI will lead to a significant amount of tech debt, but we do also recognize a lot of work in tech today is busywork and will be automated away in the hands of actual engineers with domain expertise.
How is it nonsense? Vision doesn't matter - customer feedback matters.
You start off with a hypothesis (X will solve Y's problem by doing ...), you build a prototype, and then you start testing with multiple Ys. Based on that feedback, you then tweak your initial hypothesis or you scrap it and pivot.
The whole point of engineering is to build tools that solve a specific class of problems for the buyer.
An old coworker of mine got his first job out of school with IBM.
IBM hadn't done many layoffs ever at that point and apparently didn't have system for it. He showed up on layoff day and they laid everyone off with a very generous baseline layoff package, including substantial education benefits. So he just went back to school on their dime for several years ;)
Yes it led to some degree of tech debt, but it also made it easier to experiment, validate, and identify good and bad workflows.
At least in my network, we don't think AI will replace all workers and we strongly believe AI will lead to a significant amount of tech debt, but we do also recognize a lot of work in tech today is busywork and will be automated away in the hands of actual engineers with domain expertise.